Table of Contents
Introduction (p. 2)
Chapter 1: Outsourcing (p. 4)
1.1: What is outsourcing? (p. 4)
1.2: Why do firms decide to outsource? (p. 5)
Chapter 2: Literature review (p. 7)
2.1: Globalization, Outsourcing, and Wage Inequality (Feenstra and Hanson, 1996) (p. 7)
2.2: The Impact of International Outsourcing on Employment: Empirical Evidence from EU
Countries (Falk and Wolfmayr, 2005) (p. 8)
2.3: International Outsourcing and the Productivity of Low-Skilled Labor in the EU (Egger
and Egger, 2006) (p. 9)
2.4: A New International Division of Labor in Europe: Outsourcing and Offshoring to Eastern
Europe (Marin, 2006) (p. 9)
2.5: Differences between this thesis and the reviewed literature (p. 10)
Chapter 3: Methods used to calculate outsourcing and capital intensity values (p. 11)
Chapter 4: The outsourcing patterns of Western European countries (p. 13)
4.1: France (p. 13)
4.2: Germany (p. 15)
4.3: The United Kingdom (p. 17)
Chapter 5: The outsourcing patterns of Eastern European countries (p. 19)
5.1: Bulgaria (p. 19)
5.2: Hungary (p. 21)
5.3: Slovenia (p. 23)
Conclusion (p. 25)
Literature List (p. 26)
1
Introduction
PRAGUE - Prague is turning into a center for outsourcing white-collar jobs like bookkeeping,
data-crunching and even research and development. The Czech Republic and other Central
European countries like Poland, Hungary and Slovakia are clamoring to serve the needs of
multinational corporations - and themselves. The United States may turn to India to fill many
of its call-center jobs and the like. But Western Europe is turning more frequently these days
to its own backyard, transforming a few urban centers of the former Communist bloc into the
Bangalores of Europe. (…) Outsourcing is booming as this region moves more quickly to
integrate itself economically with its more affluent neighbors to the west, reflecting progress
that is reducing the high unemployment that plagued these countries for years after the fall of
the Berlin Wall and the collapse of the Soviet empire. (…) With many of the countries of
Central Europe now in the European Union, barriers to migration have been reduced. But
most Western European countries still maintain hurdles to migrants. So instead of the people
moving to jobs in Western Europe, the jobs are moving here. (…) The wave of outsourcing is
raising sticky questions among Western European white-collar workers and their union
representatives. In 2005, when Unilever announced that it was seeking to outsource its
Western European accounting, personnel and computer activities to Eastern Europe, company
employees responded to calls from German labor leaders for a one-day walkout, fearing that
as many as 4,000 jobs would be lost. Last year, Unilever awarded lucrative contracts for the
outsourcing to IBM and Accenture, but assured the unions that jobs in the West would be
eliminated only through attrition or voluntary job changes. However, union leaders remain
skeptical. “Until now it has not been a major problem,” said Jörg Reinbrecht, who is
responsible for financial service employees at Verdi, a German union that represents many
white-collar workers. “But I think it will grow larger as Europewide banks and financial
service companies form.”
‘Eastern Europe Becomes A Center for Outsourcing’, The New York Times
Outsourcing is a topic that is often discussed. Some people say that outsourcing mainly has
positive effects, while others say that outsourcing mainly has negative effects. As the article
from the New York Times shows, the biggest fear of opponents of outsourcing is that jobs are
exported to another country. Therefore, it is important to know the outsourcing patterns of
2
countries in detail: the more outsourcing takes place in an industry, the more likely it is that
jobs in that industry are exported. In this thesis I will focus on the outsourcing patterns of
three Western European countries (France, Germany and the United Kingdom) and three
Eastern European countries (Bulgaria, Hungary and Slovenia). There are two research
questions that I am going to answer in this thesis:
1. What do the outsourcing patterns of European countries look like?
2. Do Western European countries outsource more labor intensive inputs, and do
Eastern European countries outsource more capital intensive inputs?
The second question is based on the fact that Western European countries are capital
abundant, while Eastern European countries are labor abundant.
In the first chapter, I will explain what outsourcing is, what types of outsourcing exist and
why firms decide to outsource. In the second chapter, I will provide a short literature review; I
will discuss four articles concerning outsourcing, and I will explain the difference between
these four articles and this thesis. In the third chapter I will describe the methods that I have
used to calculate both the outsourcing values and the capital intensity values for the industries
in the six countries. In the fourth chapter I will describe the top and bottom outsourcing
industries of the three Western European countries, and I will research whether it is true that
Western European countries outsource more labor intensive inputs. In the fifth chapter I will
describe the top and bottom outsourcing industries of the three Eastern European countries,
and I will research whether it is true that Eastern European countries outsource more capital
intensive products. In the conclusion I will answer the two research questions.
3
Chapter 1: Outsourcing
1.1: What is outsourcing?
The term ‘outsourcing’ is defined in many different ways. Since there is no such thing as a
universal definition of ‘outsourcing’, a problem that is also known as ‘the first set of muddles
over outsourcing’ (Bhagwati et al, 2004), this can lead to misunderstandings about the
subject. Generally speaking, outsourcing can be defined as ‘obtaining manufactured physical
inputs or service inputs from another firm’. There are four types of outsourcing, as seen below
in table 1, depending on whether both firms are located in the same country and on whether
both firms belong to the same enterprise.
Firms are located in the
Firms are located in
same country
different countries
Firms belong to the same
Onshore in-house
Offshore in-house
enterprise
outsourcing
outsourcing
Firms do not belong to the
Onshore outsourcing
Offshore outsourcing
same enterprise
Table 1: The four types of outsourcing
Onshore in-house outsourcing is the situation where a firm obtains manufactured physical
inputs or service inputs from a firm that is located in the same country and belongs to the
same enterprise.
Onshore outsourcing is the situation where a firm obtains manufactured physical inputs or
service inputs from a firm that is located in the same country and does not belong to the same
enterprise.
Offshore in-house outsourcing is the situation where a firm obtains manufactured physical
inputs or service inputs form a firm that is located in a different country and belongs to the
same enterprise.
4
Offshore outsourcing is the situation where a firm obtains manufactured physical inputs or
service inputs from a firm that is located in a different country and does not belong to the
same enterprise. This is the type of outsourcing that is discussed the most in the media.
This thesis describes the outsourcing patterns of six European countries without focusing on
whether the firms in these countries belong to the same enterprise or not. The definition of
outsourcing that is used in this thesis is thus a combination of the definitions of offshore inhouse outsourcing and offshore outsourcing; in this thesis, outsourcing is defined as the
situation where a firm obtains manufactured physical inputs or service inputs from a firm that
is located in another country.
1.2: Why do firms decide to outsource?
The decision of a firm to obtain manufactured physical inputs or service inputs from another
firm can be explained by the theory of comparative advantage by David Ricardo and the
Heckscher-Ohlin proposition by Eli Heckscher and Bertil Ohlin. In his On the Principles of
Political Economy and Taxation from 1817, Ricardo discusses an example of England and
Portugal exchanging wine and cloth to explain the theory of comparative advantage.
Labor required for
England
Portugal
120
80
100
90
producing wine
Labor required for
producing cloth
Table 2: Labor required for producing wine and cloth in England and Portugal
As table 2 shows, producing wine in Portugal requires the labor of 80 men for one year, while
producing wine in England requires the labor of 120 men for one year. Producing cloth in
Portugal requires the labor of 90 men for one year, while producing cloth in England requires
the labor of 100 men for one year. Based on a theory of absolute cost advantages, Portugal
should produce both wine and cloth, since the amount of labor required for both wine and
cloth is lower than the amount of labor required for these products in England. However, the
theory of comparative cost advantages argues that only relative (comparative) costs are import
5
for determining a nation’s production advantages; according to the theory of comparative
advantage, England should produce cloth and Portugal should produce wine.
The reasoning behind this is as follows. Producing wine in Portugal requires the labor of 80
men for one year, while producing cloth requires the labor of 90 men for one year. For
Portugal, it would thus be advantageous to export wine in exchange for cloth, since producing
wine requires less labor than producing cloth. Producing cloth in England requires the labor of
100 men for one year, while producing whine requires the labor of 120 men for one year. For
England, it would thus be advantageous to export cloth in exchange for wine, since producing
cloth requires less labor than producing wine. This can also be calculated in another way: in
Portugal, producing wine costs 0,89 cloth (80/90), while in England, producing wine costs 1,2
cloth (100/120). In Portugal, producing cloth costs 1,125 wine (90/80), while in England,
producing cloth costs 0,83 wine (100/120). Ricardo therefore argues that it is beneficial for
Portugal to specialize in the production of wine and exchange the wine for cloth from
England, while it is beneficial for England to specialize in the production of cloth and
exchange the cloth for wine from Portugal. Ricardo’s theory of comparative advantage shows
why countries decide to import goods and/or services from other countries.
In this thesis, the main question that is answered is: do Western European countries, which are
relatively capital abundant, outsource more labor intensive inputs, while Eastern European
countries, which are relatively labor abundant, outsource more capital intensive inputs? This
proposition is also known as the Heckscher-Ohlin proposition, one of the main results of the
neoclassical trade theory. This proposition relates the abundance of the factors of production
in a region or country and the international trade flows of goods and services (Van Marrewijk,
2002). According to the Hecksher-Ohlin proposition, in a neoclassical framework with two
final goods, two factors of production and two countries which have identical homothetic
tastes, a country will export the good which intensively uses the relatively abundant factor of
production. This means that, if a country is relatively capital abundant, it will export capital
intensive goods and/or services; if a country is relatively labor abundant, it will export labor
intensive goods and/or services. When applied to outsourcing, this means that, if a country is
relatively capital abundant, it will mostly outsource labor intensive goods and/or services; if a
country is relatively labor abundant, it will mostly outsource capital intensive goods and/or
services.
6
Chapter 2: Literature review
2.1: Globalization, Outsourcing, and Wage Inequality (Feenstra and Hanson, 1996)
In their paper, Feenstra and Hanson extend previous work on the impact of outsourcing on the
relative demand for skilled labor by incorporating new data on manufactured imports. They
do this by combining import data from the National Bureau of Economic Research with data
on input purchases from the Census of Manufacturers to construct industry-by-industry
estimates of outsourcing for the period 1972-1992. Feenstra and Hanson measure outsourcing
(So) as “the share of imported intermediate inputs in the total purchase of non-energy
materials”:
with
with
Thus,
The definition which Feenstra and Hanson use is more general than that which appears in the
literature before 1996. The measurement for input purchases by Feenstra and Hanson includes
two types of intermediate inputs: (i) parts and components and (ii) contract work done by
others. The second category includes goods that are produced entirely by subcontractors, with
the US manufacturer attaching its brand name to a finished product. Also included in this
7
category is the use of foreign plants for product assembly. In contrast, Berman et al. (1994)
defined outsourcing to include only parts and components purchased from abroad. Also,
Feenstra and Hanson do not limit outsourcing to mean the foreign activities of multinational
corporations, as Lawrence (1994) and Slaughter (1995) did. Lawrence and Slaughter
measured outsourcing by using the purchase of inputs by multinationals from foreign
subsidiaries; Feenstra and Hanson think it is somewhat arbitrary to ignore the transactions
between firms and independent foreign suppliers, since companies now import parts and
components that they could have produced domestically.
Feenstra and Hanson then show regression results for the change in the nonproduction wage
share for two periods (1972-1979 and 1979-1990). These results show that outsourcing is
positively correlated with the change in the relative employment of nonproduction workers,
but weakly negatively correlated with the change in relative average annual earnings of
nonproduction workers.
2.2: The Impact of International Outsourcing on Employment: Empirical Evidence
from EU Countries (Falk and Wolfmayr, 2005)
Falk and Wolfmayr investigate the impact of international outsourcing on total employment
by using manufacturing data for seven EU countries for the period 1995-2000. The main
question they want to answer is whether imported materials are a complement or a substitute
for domestic employment. In their model, Falk and Wolfmayr use a narrow measure of
outsourcing, defining outsourcing as “importing intermediate goods from the same industry”.
They combine trade statistics for goods imports with information from input-output tables to
identify imported intermediates by their country of origin, distinguishing between imported
materials from low-wage countries and high-wage countries. Falk and Wolfmayr also
investigate whether the degree of outsourcing differs across industries. Their results show that
imports from low-wage countries have a statistically significant and negative impact on
employment; rising imports from low-wage countries account for approximately 0.25
percentage points employment reduction per year. Imports from industrialized countries have
no effect on employment. The magnitude of the effect differs across industries: in some
industries, the impact of imported materials from low-wage countries is not statistically
different from zero.
8
2.3: International Outsourcing and the Productivity of Low-Skilled Labor in the EU
(Egger and Egger, 2006)
In their paper, Egger and Egger examine the role of international outsourcing on the
productivity of low-skilled workers in EU manufacturing. They do this by constructing a
narrow measure of outsourcing by combining trade statistics for intermediate goods imports
and information from input-output tables. This measure of outsourcing (Otic) is defined as
follows:
with
Dic = the diagonal of the NACE two-digit input-output tables as a share of total intermediates
usage by that industry for each EU economy;
Mtic = real gross production;
Ytic = NACE two-digit real intermediate goods imports.
Egger and Egger find that, in the short run, outsourcing has a significant negative marginal
effect on real value added per low-skilled worker. In the long run, however, outsourcing has a
positive impact on real value added per low-skilled worker. Egger and Egger also state that
there is evidence that international outsourcing augments physical capital and high-skilled
labor (both relative to low-skilled labor) to roughly the same extent in the short run as well as
the long run.
2.4: A New International Division of Labor in Europe: Outsourcing and Offshoring to
Eastern Europe (Marin, 2006)
In her paper, Marin examines changes in Europe’s international organization of production by
researching survey data of Austrian and German firms investing in Eastern Europe. According
to Marin, Europe is reorganizing its international value chain by outsourcing and offshoring
production to Eastern Europe; as a result, Eastern Europe is becoming an important location
for the international organization of production of European firms. Marin defines outsourcing
9
as “a relocation of activity outside the firm to an independent input supplier in New Europe”;
offshoring is defined as “a relocation to New Europe of activity that remains inside the firm”.
Marin then focuses on the offshoring activities of Germany and Austria to Eastern Europe. On
average, about 45% of German investment to Eastern Europe are offshoring activities of
German firms; about 17% of Austrian investment to Eastern Europe are offshoring
investments. Marin then focuses on intrafirm trade with Eastern Europe; in Germany, 21.6%
of imports from and 11.7% of exports to Eastern Europe are intrafirm transactions, in Austria
these numbers are 68.5% and 22.4%, respectively. She concludes that the pattern of intrafirm
trade that has emerged between Germany and Eastern Europe and between Austria and
Eastern Europe suggests that some of the European countries have clearly become new
members in the international division of labor. Finally, Marin uses regression analysis to
determine the driving force behind offshoring and outsourcing in Germany and Austria. The
results show that German firms want to offshore to a low-wage country when labor costs
matter and transport costs are not too high; also, German outsourcing to Eastern Europe
(relative to offshoring) is more likely when the parent firm is more capital intensive and less
R&D intensive, when transport costs are larger and when the host country has a low level of
corruption. Austrian firms are more likely to offshore when they are less R&D intensive and
when they are capital intensive (rather than labor intensive).
2.5: Differences between this thesis and the reviewed literature
In their articles, Feenstra and Hanson and Egger and Egger focus on the impact of outsourcing
(on employment rates), while I focus on the driving forces behind outsourcing by researching
whether an abundance of a certain factor of production leads to a certain outsourcing pattern.
Marin and Falk and Wolfmayr do discuss the driving forces behind outsourcing; however, the
outsourcing patterns Marin constructs for two European countries (Germany and Austria) are
geography-based (what country are jobs exported to?), while the outsourcing patterns I have
constructed are industry-based (jobs from which industries are exported?). Falk and
Wolfmayr only focus on manufacturing when constructing outsourcing patterns, looking at a
smaller number of industries than I do; also, their main focus is on changes in time of the
outsourcing patterns (relative numbers), while I focus on (absolute) numbers in one year.
10
Chapter 3: Methods used to calculate outsourcing and capital intensity
values
In this chapter I will explain what methods I have used to calculate the outsourcing data for
the six European countries and the capital intensity of the industries in these countries.
To calculate the outsourcing numbers, I have used the formula for globalization that is used
by Feenstra and Hanson in their article called ‘Globalization, Outsourcing, and Wage
Inequality (see chapter 2):
The EUROSTAT European System of Accounts (ESA) 95 has constructed input-output tables
which include information for different years on supply and demands of goods and services
and foreign trade, amongst others. I have used the data from these input-output tables to
construct the input purchases from the different industries, imports, shipments and the total
purchase of non-energy materials.
The industries for which I have calculated the outsourcing numbers are so called NACEindustries. NACE (Nomenclature statistique des activtés économiques dans la Communauté
européenne) is a code which is constructed by the EU to describe certain classes of
economical activities. Since some data is missing for some of the NACE-industries, I have
removed these industries from the outsourcing patterns. I have decided to calculate the
outsourcing numbers for 2003, since not all numbers were available for all six countries for
2004 or 2005.
To research if developed countries outsource more labor intensive inputs while less
developed countries outsource more capital intensive inputs, I have used the article called
‘Factor Content, Size, and Export Propensity at the Firm Level’ by Philip Vermeulen to
calculate the capital intensity for the different industries in the six European countries. In his
paper, Vermeulen tests both the factor content (or comparative advantage) and economies of
scale theories of trade by using micro firm data. The first theory, as I have shown in chapter 1
11
of this thesis, predicts that countries will export goods and services which intensively use
relatively abundant factors of production in their production. The second theory stresses size
as a factor in explaining export propensity; only firms that are large enough can reap the
benefits of economies of scale. Vermeulen measures capital intensity as “value added minus
labor costs divided by the number of employees”. Since the number of employees are not
available for all of the six countries that I am researching, I have decided to replace the
number of employees by the value of total output for the industry. Thus, I will measure capital
as value added minus labor costs, divided by the total output for the industry.
In chapter 4 and 5, I will provide the outsourcing values (OV) and capital intensity values (CI)
for the industries in the six European countries, as well as a prediction equation for the
outsourcing values. Since I assume that Western European countries (which are capital
abundant) outsource more labor intensive inputs, I would expect the coefficient of capital
intensity to be negative: when an industry in a Western European country has a low capital
intensity, the outsourcing value is expected to be high, and when an industry has a high
capital intensity, the outsourcing value is expected to be low. Since I assume that Eastern
European countries (which are labor abundant) outsource more capital intensive inputs, I
would expect the coefficient of capital intensity to be positive: when an industry in a Eastern
European country has a high capital intensity, the outsourcing value is expected to be high,
and when an industry has a low capital intensity, the outsourcing value is expected to be low.
In chapters 4 and 5, I will also provide the R2 coefficients and the t-values of the prediction
equations. The R2 coefficient measures how well the regression line approximates the real
data points. Values of R2 can range from zero to one; the higher the value is to one, the better
the regression line fits the data. The P-value reports the result of a significance test for the
coefficients; when the P-value is smaller than .05, the coefficient can be considered to have a
significant effect.
12
Chapter 4: The outsourcing patterns of Western European countries
4.1: France
Top outsourcing industries
OV
CI
Coal and lignite; peat
13,700
0.14
Crude petroleum and natural gas
10,407
0.41
Metal ores
9,549
0.19
Tobacco products
8,290
0.44
Fish and other fishing products
8,254
0.53
Office machinery and computers
6,868
0.12
Wearing apparel; furs
6,623
0.12
Supporting and auxiliary transport services
6,425
0.19
Furniture
6,290
0.12
Leather and leather products
6,133
0.16
Bottom outsourcing industries
OV
CI
Motor vehicles and (semi-)trailers
4,361
0.08
Food products and beverages
4,254
0.11
Financial intermediation services
4,157
0.19
Land transport; transport via pipeline services
4,098
0.17
Health and social work services
3,721
0.24
Other transport equipment
3,563
0.07
Air transport services
3,505
0.04
Research and development services
3,202
0.03
Electrical energy, gas, steam and hot water
2,453
0.26
Water transport services
1,160
0.06
13
12500.00
OV
10000.00
7500.00
5000.00
2500.00
0.00
0.00
0.10
0.20
0.30
0.40
0.50
0.60
CI
Since France is assumed to be capital abundant, the impact of capital intensity on outsourcing
is expected to be negative. According to SPSS, the predicted equation to determine
outsourcing is: OV = 4404 + 7000 × CI. The value of R2 is 0.141; the P-values for the
constant and for CI are .000 and .013, respectively. Since capital intensity has a positive
impact on outsourcing, it can not be concluded that France outsources more labor intensive
products.
14
4.2: Germany
Top outsourcing industries
OV
CI
Crude petroleum and natural gas
9,837
0.25
Construction work
9,564
0.15
Other services
9,421
0.60
Real estate services
8,735
0.74
Services auxiliary to financial intermediation
8,334
0.29
Products of agriculture and hunting
8,025
0.22
Recreational, cultural and sporting services
7,526
0.29
Wearing apparel; furs
6,922
0.10
Leather and leather products
6,879
0.11
Post and telecommunication services
6,866
0.33
Bottom outsourcing industries
OV
CI
Rubber and plastic products
4,135
0.12
Air transport services
3,964
0.07
Fabricated metal products
3,950
0.12
Medical, precision and optical instruments
3,804
0.13
Printed matter and recorded media
3,611
0.18
Insurance and pension funding services
3,438
0.02
Motor vehicles and (semi-)trailers
3,224
0.06
Tobacco products
3,137
0.21
Machinery and equipment n.e.c.
3,009
0.08
Water transport services
1,345
0.28
15
10000.00
8000.00
OV
6000.00
4000.00
2000.00
0.00
0.00
0.20
0.40
0.60
0.80
CI
Since Germany is assumed to be capital abundant, the impact of capital intensity on
outsourcing is expected to be negative. According to SPSS, the predicted equation to
determine outsourcing is: OV = 4403 + 6115 × CI. The value of R2 is 0.215; the P-values for
the constant and for CI are .000 and .001, respectively. Since capital intensity has a positive
impact on outsourcing, it can not be concluded that Germany outsources more labor intensive
products.
16
4.3: United Kingdom
Top outsourcing industries
OV
CI
Electrical energy, gas, steam and hot water
10,459
0.22
Coal and lignite; peat
10,258
0.13
Renting services of machinery and equipment
9,747
0.28
Sewage and refuse disposal services
9,561
0.19
Wood and products of wood and cork
8,934
0.14
Products of agriculture and hunting
8,357
0.32
Leather and leather products
8,147
0.17
Products of forestry and logging
8,092
0.15
Wearing apparel; furs
8,031
0.08
Pulp, paper and paper products
7,395
0.09
Bottom outsourcing industries
OV
CI
Other business services
3,536
0.21
Construction work
3,468
0.19
Water transport services
3,431
0.07
Other services
3,395
0.31
Computer and related services
3,127
0.14
Education services
2,729
0.05
Research and development services
2,542
0.09
Services auxiliary to financial intermediation
873
0.11
Insurance and pension funding services
579
0.27
Public administration and defence services
261
0.07
17
12000.00
10000.00
OV
8000.00
6000.00
4000.00
2000.00
0.00
0.00
0.20
0.40
0.60
0.80
CI
Since the United Kingdom is assumed to be capital abundant, the impact of capital intensity
on outsourcing is expected to be negative. According to SPSS, the predicted equation to
determine outsourcing is: OV = 5452 + 313 × CI. The value of R2 is 0.000; the P-values for
the constant and for CI are .000 and .896, respectively. Even though the P-value for CI is
greater than .05, which means that its value is not significantly different from 0, it can not be
concluded that CI is smaller than 0, as would be expected for a capital abundant country.
Therefore, it can not be concluded that the United Kingdom outsources more labor intensive
products.
18
Chapter 5: The outsourcing patterns of Eastern European countries
5.1: Bulgaria
Top outsourcing industries
OV
CI
Coal and lignite; peat
17,019
0.12
Motor vehicles and (semi-)trailers
10,219
0.08
Radio, television and communication equipment
9,144
0.26
Office machinery and computers
9,108
0.17
Other business services
8,762
0.20
Rubber and plastic products
8,555
0.14
Insurance and pension funding services
8,520
0.27
Medical, precision and optical instruments
8,282
0.24
Printed matter and recorded media
7,829
0.14
Renting services of machinery and equipment
7,806
0.40
Bottom outsourcing industries
OV
CI
Basic metals
3,788
0.06
Post and telecommunication services
3,202
0.54
Wood and products of wood and cork
2,846
0.10
Products of agriculture and hunting
2,796
0.45
Construction work
2,776
0.18
Water transport services
2,456
0.03
Wearing apparel; furs
1,441
0.20
Supporting and auxiliary transport services
1,284
0.07
Real estate services
860
0.90
Public administration and defence services
450
0.07
19
20000.00
OV
15000.00
10000.00
5000.00
0.00
0.00
0.20
0.40
0.60
0.80
1.00
CI
Since Bulgaria is assumed to be a labor abundant country, the impact of capital intensity on
outsourcing is expected to be positive. According to SPSS, the predicted equation to
determine outsourcing is: OV = 6446 - 3276 × CI. The value of R2 is 0.030; the P-values for
the constant and for CI are .000 and .269, respectively. Even though the P-value for CI is
greater than .05, which means that its value is not significantly different from 0, it can not be
concluded that CI is greater than 0, as would be expected for a labor abundant country.
Therefore, it can not be concluded that Bulgaria outsources more capital intensive products.
20
5.2: Hungary
Top outsourcing industries
OV
CI
Metal ores
14,332
0.13
Coal and lignite; peat
11,356
0.08
Crude petroleum and natural gas
10,561
0.14
Electrical energy, gas, steam and hot water
9,658
0.19
Other mining and quarrying products
8,835
0.25
Insurance and pension funding services
8,707
0.17
Tobacco products
7,935
0.25
Printed matter and recorded media
7,560
0.11
Renting services of machinery and equipment
7,487
0.57
Financial intermediation services
7,121
0.19
Office machinery and computers
4,407
0.08
Motor vehicles and (semi-)trailers
4,175
0.12
Land transport; transport via pipeline services
4,070
0.13
Food products and beverages
3,729
0.10
Wearing apparel; furs
3,458
0.06
Supporting and auxiliary transport services
3,408
0.27
Products of agriculture and hunting
3,256
0.19
Products of forestry and logging
2,638
0.11
Wholesale trade and commission trade services
1,858
0.20
Secondary raw materials
510
0.06
Bottom outsourcing industries
21
14000.00
12000.00
OV
10000.00
8000.00
6000.00
4000.00
2000.00
0.00
0.00
0.10
0.20
0.30
0.40
0.50
0.60
CI
Since Hungary is assumed to be a labor abundant country, the impact of capital intensity on
outsourcing is expected to be positive. According to SPSS, the predicted equation to
determine outsourcing is: OV = 5735 + 2432 × CI. The value of R2 is 0.010; the P-values for
the constant and for CI are .000 and .525, respectively. Since capital intensity has a positive
impact on outsourcing, it can be concluded that Hungary outsources more capital intensive
products; however, because the P-value is greater than .05, this is not significant.
22
5.3: Slovenia
Top outsourcing industries
OV
CI
Products of agriculture and hunting
8,979
0.34
Office machinery and computers
8,924
0.12
Other mining and quarrying products
8,888
0.21
Education services
8,355
0.07
Public administration and defence services
8,249
0.15
Recreational, cultural and sporting services
7,095
0.18
Leather and leather products
6,782
0.02
Products of forestry and logging
6,725
0.24
Financial intermediation services
6,667
0.35
Basic metals
6,549
0.09
Bottom outsourcing industries
OV
CI
Fabricated metal products
4,786
0.13
Rubber and plastic products
4,708
0.15
Machinery and equipment n.e.c.
4,528
0.11
Electrical machinery and apparatus n.e.c.
4,526
0.10
Printed matter and recorded media
4,264
0.13
Wholesale trade and commission trade services
3,840
0.21
Wood and products of wood and cork
3,790
0.10
Furniture
2,499
0.12
Air transport services
780
0.13
Water transport services
417
0.25
23
10000.00
8000.00
OV
6000.00
4000.00
2000.00
0.00
0.00
0.20
0.40
0.60
0.80
CI
Since Slovenia is assumed to be a labor abundant country, the impact of capital intensity on
outsourcing is expected to be positive. According to SPSS, the predicted equation to
determine outsourcing is: OV = 5371 + 1046 × CI. The value of R2 is 0.005; the P-values for
the constant and for CI are .000 and .658, respectively. Since capital intensity has a positive
impact on outsourcing, it can be concluded that Slovenia outsources more capital intensive
products; however, because the P-value is greater than .05, this is not significant.
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Conclusion
In this thesis I have described the outsourcing patterns of six European countries: three
Western European countries (France, Germany and the United Kingdom) and three Eastern
European countries (Bulgaria, Hungary and Slovenia). Instead of renaming the 120 industries
that form the top and bottom outsourcing industries for the six countries, I will refer to chapter
four and five for the description of the outsourcing patterns.
In this thesis I have also answered the following question: do Western European countries
outsource more labor intensive inputs (since they are capital abundant countries), and do
Eastern European countries outsource more capital intensive inputs (since they are labor
abundant countries)? To answer this question, I have calculated the prediction equation for the
outsourcing values for the six countries. Since Western European countries are capital
abundant, I would expect that capital intensity has a negative impact on outsourcing in these
countries; since Eastern European countries are labor abundant, I would expect that capital
intensity has a positive impact on outsourcing in these countries, as I have shown in chapter
three. In chapter four and five I have shown, based on the outsourcing values and capital
intensities of the industries in the six countries, that only Hungary and Slovenia are in sync
with the assumptions that Western European countries outsource more labor intensive inputs
and that Eastern European countries outsource more capital intensive inputs; however, for
both countries the effects were not significant. In other words, based on the available data, I
have found that the Heckscher-Ohlin proposition (applied to outsourcing) only holds for two
of the six countries (again, these effects were not significant); according to the data, it cannot
be concluded that Western European countries outsource relatively more labor intensive
inputs, since none of the three countries show this. On the other hand, the data shows that two
of the three Eastern European countries outsource relatively more capital intensive inputs,
which is in line with the Heckscher-Ohlin proposition (applied to outsourcing), but these
effects are not significant.
25
Literature List
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Perspectives, 18(4), 93-114
Egger, H. and P. Egger (2006), ‘International Outsourcing and the Productivity of LowSkilled Labor in the EU’, Economic Inquiry, 44(1), 98-108
EUROSTAT, ESA 95 Input-Output tables
Falk, M. and Y. Wolfmayr (2005), ‘The Impact of International Outsourcing on Employment:
Empirical Evidence from EU Countries’, Austrian Institute of Economic Research
Feenstra, R.C. and G.H. Hanson (1996), ‘Globalization, Outsourcing, and Wage Inequality’,
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Marin, D. (2006), ‘A New International Division of Labor in Europe: Outsourcing and
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